The Reconfigurable Future of Healthcare
Data plays a more central role in healthcare than ever before. It won’t be long before every person’s genome is sequenced at birth, with follow-up sequencing done at regular intervals throughout life. Each genomic check-up would produce roughly 180 gigabytes of data that will need to be processed, analyzed, and stored. The promise of using such data is that doctors would be able to intercept diseases before symptoms develop, taking preventative medicine to a whole new level.
Already, whole-genome sequencing is helping to diagnose otherwise-hidden diseases, while machine-learning tools can enhance a doctor’s decision-making by scouring reams of data with speed and accuracy that far surpasses human capabilities. Meanwhile, the advent of wearable sensors is generating an unprecedented amount of additional data, including heart rate, respiration, blood pressure, and other vital signs. No wonder we stand at the threshold of healthcare’s “era of data.”
Big data is at the center of this whirlwind, but putting all this data to good use has been another matter altogether. What we have been missing, until recently, has been ample computing power.
In order to handle the surge of useful health care data—genomic and otherwise— available to us, we must adopt more powerful computing tools than the CPU-based machines that have dominated the computer and server industries for decades. Unless we do so, we will continue to face a data bottleneck that stands in the way of quick answers for healthcare providers and researchers.
Fortunately, an answer exists in a technology that has actually been available for decades —FPGAs, or field-programmable gate arrays—which are now going mainstream. Why now? In the past, programming these chips required significant expertise. Now, however, computing demands have reached a point where the efficiency of an FPGA outweighs programming hurdles. The increased use of FPGAs has in turn lowered costs, further accelerating mass adoption.
How do FPGAs achieve such efficiency? It comes down to design. Instead of the many lines of software code that are … Next Page »